Information pushing method and device

ABSTRACT

Embodiments can include an information pushing method and device. An embodiment of the method can include: receiving an information stream data acquisition request sent by a terminal, wherein the information stream data acquisition request comprises query information; performing a query according to the query information to obtain first information stream data; acquiring at least one of a search record or a browsing record of an account associated with the terminal with respect to a predetermined time period; determining, based on the at least one of the search record or the browsing record, a keyword; determining second information stream data located in a preset information stream data set and matching the key word; generating, based on the first information stream data and the determined second information stream data, data to be pushed; and pushing to the terminal the data to be pushed. The embodiment can achieve targeted information pushing.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of International Application No.PCT/CN2017/118007, filed on Dec. 22, 2017, which claims priority toChinese Patent Application No. “201710351701.3” filed on May 18, 2017.All of the aforementioned applications are hereby incorporated byreference in their entireties.

TECHNICAL FIELD

The present disclosure relates to the field of computer technologies,and in particular to a method and apparatus for pushing information.

BACKGROUND

With the development of network technologies, at present many productssuch as search engines, Blog, SNS (Social Network Site) or RSS (ReallySimple Syndication), publish information stream data by usinginformation stream (Feed) systems. Information stream data refers to asyndicated feed, and may also be referred to as a source feed, a feed, anews feed, syndication, an abstract, a source, a news subscription, aweb feed, etc. A website may transmit the latest information to usersthrough the information stream data, and the prerequisite that users cansubscribe the website is that the website is capable of providingcontinuously updated information. The advantage of information streampresentation lies in that it allows users to see the latest data everytime they query, and the experience is much better than that of theconventional open and display presentation.

In the prior art, when a user enters a page that carries informationstream data, in addition to the information subscribed by the user, theserver may also pushes other information to the user, for example, eventinformation of a recent event held by the website or advertisementinformation. However, the other information pushed to the user by theserver is usually not what the user needs and lacks pertinence.

SUMMARY

Some embodiments of the present disclosure are directed to providing animproved method and apparatus for pushing information, to solve thetechnical problems mentioned in the background.

In a first aspect, embodiments of the present disclosure provide amethod for pushing information, the method including: receiving aninformation stream data acquisition request sent by a terminal, theinformation stream data acquisition request including query information;performing a query according to the query information to obtain firstinformation stream data; acquiring a search record and/or a browsingrecord of an account associated with the terminal, the search recordand/or the browsing record being within a predetermined time period;determining a keyword based on the search record and/or the browsingrecord; determining, in a preset information stream data set, secondinformation stream data matching the keyword; generating to-be-pusheddata based on the first information stream data and the determinedsecond information stream data; and pushing the to-be-pushed data to theterminal.

In this embodiment, the determining a keyword based on the search recordand/or the browsing record includes: acquiring a search statement in thesearch record and/or a content of a browsed page in the browsing record;parsing the search statement and/or the content, to obtain analternative word set; for each alternative word in the alternative wordset, determining, in a preset information stream data set, secondinformation stream data matching the alternative word; determining, on abasis of a pre-trained first probability determination model, a firstprobability of receiving a visit request for a page sent by theterminal, where the page includes a page pointed to by the secondinformation stream data matching the alternative word, and the firstprobability determination model is used to characterize a correspondingrelationship between at least one of the following information items andthe first probability: account information of an account associated withthe terminal, a device type of the terminal, a browser type of a browserused by the terminal, the alternative word, information of an industryto which the alternative word belongs, or source of the alternativeword; and selecting the keyword from the alternative word set based onthe first probability.

In this embodiment, for each piece of information stream data in thepreset information stream data set, an attribute value corresponding tothe piece of information stream data is preset; and the selecting thekeyword from the alternative word set based on the first probabilityincludes: for each alternative word in the alternative word set,executing the following score determination operations: acquiring apreset attribute value corresponding to the second information streamdata matching the alternative word, and determining, based on theacquired attribute value, an attribute value corresponding to thealternative word; calculating a product of the attribute valuecorresponding to the alternative word and the first probabilitycorresponding to the alternative word; acquiring weights preset for thefirst probability, the attribute value and the product, and performing,according to the acquired weights, weighted summation on the attributevalue corresponding to the alternative word, the first probabilitycorresponding to the alternative word, and the product to obtain a scorecorresponding to the alternative word; and selecting, from therespective alternative words of the alternative word set, apredetermined number of alternative words as keywords according to anorder of the scores from high to low.

In this embodiment, the parsing the search statement and/or the contentto obtain an alternative word set includes: performing statisticalanalysis and/or semantic parsing on the search statement and/or thecontent, to extract at least one core word; expanding each core word inthe at least one core word to obtain an expanded word, where theexpanded word includes at least one of the following: a synonym of thecore word, a near-synonym of the core word, or an associated word of thecore word; and determining the core word and the obtained expanded wordas keywords.

In this embodiment, the generating to-be-pushed data based on the firstinformation stream data and the determined second information streamdata includes: in response to the number of the determined secondinformation stream data being greater than a preset number, executingthe following score determination operation for each piece of secondinformation stream data in the determined second information streamdata: acquiring a preset attribute value corresponding to the secondinformation stream data; respectively determining, on a basis of apre-trained second probability determination model, a second probabilityof receiving a request sent by the terminal for visiting a page pointedto by the second information stream data, where the second probabilitydetermination model is used to characterize a corresponding relationshipbetween at least one of the following information items and the secondprobability: account information of an account associated with theterminal, a device type of the terminal, type information of a browserused by the terminal, or feature information of the second informationstream data; and determining a score of the second information streamdata based on the acquired attribute value and the second probability;selecting, from the determined second information stream data, a presetnumber of second information stream data according to an order of thescores from high to low i; and aggregating the first information streamdata and the selected second information stream data to generateto-be-pushed data.

In a second aspect, the embodiments of the present disclosure provide anapparatus for pushing information, the apparatus including: a receivingunit, configured to receive an information stream data acquisitionrequest sent by a terminal, the information stream data acquisitionrequest including query information; a query unit, configured to performa query according to the query information to obtain first informationstream data; an acquisition unit, configured to acquire a search recordand/or a browsing record of an account associated with the terminal, thesearch record and/or the browsing record being within a predeterminedtime period; a first determination unit, configured to determine akeyword based on the search record and/or the browsing record; a seconddetermination unit, configured to determine second information streamdata matching the keyword in a preset information stream data set; ageneration unit, configured to generate to-be-pushed data based on thefirst information stream data and the determined second informationstream data; and a push unit, configured to push the to-be-pushed datato the terminal.

In this embodiment, the first determination unit includes: anacquisition subunit, configured to acquire a search statement in thesearch record and/or content of a browsed page in the browsing record;an analysis subunit, configured to parse the search statement and/or thecontent, to obtain an alternative word set; a first determinationsubunit, configured to determine, for each alternative word in thealternative word set, in a preset information stream data set, secondinformation stream data matching the alternative word, and determine, ona basis of a pre-trained first probability determination model, a firstprobability of receiving a visit request for a page sent by theterminal, where the page includes a page pointed to by the secondinformation stream data matching the alternative word, and the firstprobability determination model is used to characterize a correspondingrelationship between at least one of the following information items andthe first probability: account information of an account associated withthe terminal, a device type of the terminal, a browser type of a browserused by the terminal, the alternative word, information of an industryto which the alternative word belongs, or source of the alternativeword; and a first selection subunit, configured to select the keywordfrom the alternative word set based on the first probability.

In this embodiment, for each piece of information stream data in thepreset information stream data set, an attribute value corresponding tothe piece of information stream data is preset; and the first selectionsubunit includes: a first determination module, configured to executethe following score determination operations for each alternative wordin the alternative word set: acquiring a preset attribute valuecorresponding to the second information stream data matching thealternative word, and determining, based on the acquired attributevalue, an attribute value corresponding to the alternative word;calculating a product of the attribute value corresponding to thealternative word and the first probability corresponding to thealternative word; acquiring weights preset for the first probability,the attribute value and the product, and performing, based on theacquired weight, weighted summation on the attribute value correspondingto the alternative word, the first probability corresponding to thealternative word, and the product to obtain a score corresponding to thealternative word; and a selection module, configured to select, fromrespective alternative words of the alternative word set, apredetermined number of alternative words as keywords according to anorder of the scores from high to low.

In this embodiment, the analysis subunit includes: an analysis module,configured to perform statistical analysis and/or semantic parsing onthe search statement and/or the content, to extract at least one coreword; an expansion module, configured to expand each core word in the atleast one core word to obtain an expanded word, where the expanded wordincludes at least one of the following: a synonym of the core word, anear-synonym of the core word, or an associated word of the core word;and a second determination module, configured to determine the core wordand the obtained expanded word as keywords.

In this embodiment, the generation unit includes: a second determinationsubunit, configured to execute, in response to the number of thedetermined second information stream data being greater than a presetnumber, the following score determination operation for each piece ofsecond information stream data in the determined second informationstream data: acquiring a preset attribute value corresponding to thesecond information stream data; respectively determining, on a basis ofa pre-trained second probability determination model, a secondprobability of receiving a request sent by the terminal for visiting apage pointed to by the second information stream data, where the secondprobability determination model is used to characterize a correspondingrelationship between at least one of the following information items andthe second probability: account information of an account associatedwith the terminal, a device type of the terminal, type information of abrowser used by the terminal, or feature information of the secondinformation stream data; and determining a score of the secondinformation stream data based on the acquired attribute value and thesecond probability; a second selection subunit, configured to select,from the determined second information stream data, a preset number ofsecond information stream data according to an order of the scores fromhigh to low; and an aggregation subunit, configured to aggregate thefirst information stream data and the selected second information streamdata to generate to-be-pushed data.

In a third aspect, the embodiments of the present disclosure provide adevice, including: one or more processors; and a storage apparatus,configured to store one or more programs, where when the one or moreprograms are executed by the one or more processors, the one or moreprocessors implement the method described in the first aspect.

In a fourth aspect, the embodiments of the present disclosure provide acomputer readable storage medium on which computer programs are stored,where when the programs are executed by processors, the method in thefirst aspect is implemented.

The method and apparatus for pushing information according to theembodiments of the present disclosure realize targeted information pushby receiving an information stream data acquisition request sent by aterminal, performing a query according to the query information toobtain first information stream data, then acquiring a search record anda browsing record of an account associated with the terminal, the searchrecord and/or the browsing record being within a predetermined timeperiod, determining a keyword based on the search record and/or thebrowsing record, determining second information stream data matching thekeyword in a preset information stream data set, finally generatingto-be-pushed data based on the first information stream data and thedetermined second information stream data, and pushing the to-be-pusheddata to the terminal.

BRIEF DESCRIPTION OF THE DRAWINGS

Other features, objectives and advantages of the present disclosure willbecome more apparent by reading detailed descriptions of non-restrictiveembodiments made with reference to the following drawings:

FIG. 1 is a system architecture diagram to which some embodiments of thepresent disclosure can be applied;

FIG. 2 is a schematic flowchart of an embodiment of a method for pushinginformation;

FIG. 3 is a schematic flowchart of another embodiment of the method forpushing information;

FIG. 4 is a schematic diagram of an application scenario of the methodfor pushing information according to an embodiment;

FIG. 5 is an example structure diagram of an embodiment of an apparatusfor pushing information; and

FIG. 6 is a structure diagram of a computer system of a server suitablefor implementing some embodiments.

DETAILED DESCRIPTION OF EMBODIMENTS

The present disclosure will be further described below in detail incombination with the accompanying drawings and the embodiments. Itshould be appreciated that the specific embodiments described herein aremerely used for explaining the relevant disclosure, rather than limitingthe disclosure. In addition, it should be noted that, for the ease ofdescription, only the parts related to the relevant disclosure are shownin the accompanying drawings.

It should also be noted that the embodiments in the present disclosureand the features in the embodiments may be combined with each other on anon-conflict basis. The present disclosure will be described below indetail with reference to the accompanying drawings and in combinationwith the embodiments

FIG. 1 shows a system architecture 100 to which some embodiments of amethod for pushing information or an apparatus for pushing informationaccording to the present disclosure can be applied.

As shown in FIG. 1, the system architecture 100 may include terminaldevices 101, 102 and 103, a network 104, and a server 105. The network104 is configured to provide a medium of a communication link betweenthe terminal devices 101, 102 and 103 and the server 105. The network104 may include various connection types, such as wired or wirelesscommunication links or optical fiber cables.

A user may interact with the server 105 by using the terminal device101, 102 or 103 through the network 104 to receive or send messages,etc. A variety of applications, such as web browser applications,shopping applications, search applications, instant messaging tools,e-mail clients and social platform software, may be installed on theterminal devices 101, 102 and 103.

The terminal devices 101, 102 and 103 may be various types of electronicdevices with display screens and supporting text entry, including butnot limited to a smart phone, a tablet computer, an e-book reader, anMP3 player (Moving Picture Experts Group Audio Layer III), an MP4 player(Moving Picture Experts Group Audio Layer IV), a laptop computer, adesktop computer, etc.

The server 105 may be a server providing various services, for example,a background server providing a support for an application using aninformation stream system on the terminal 101, 102 or 103. The server105 may receive an information stream data acquisition request sent bythe terminal device 101, 102 or 103, perform a query according to thequery information to obtain first information stream data, acquire asearch record and a browsing record of an account associated with theterminal, the search record and the browsing record being within apredetermined time period, determine a keyword based on the searchrecord and/or the browsing record, determine, in a preset informationstream data set, second information stream data matching the keyword,finally generate to-be-pushed data based on the first information streamdata and the determined second information stream data, and push theto-be-pushed data to the terminal device 101, 102 or 103.

It should be noted that the method for pushing information, provided bythe embodiments of the present disclosure, may be executed by the server105, and accordingly, the apparatus for pushing information may bearranged in the server 105.

It should be appreciated that the numbers of the terminal devices, thenetwork and the server in FIG. 1 are only schematic. According to animplementation requirement, any number of terminal devices, networks andservers may be provided.

Continue to refer to FIG. 2, which shows a process 200 of an embodimentof the method for pushing information. The method for pushinginformation includes the following steps:

Step 201: receiving an information stream data acquisition request sentby a terminal.

In this embodiment, an electronic device (e.g., the server shown inFIG. 1) on which the method for pushing information runs may receive aninformation stream data acquisition request sent by a terminal.

The information stream data acquisition request may be a request sent bythe terminal when an application using an information stream data systemis started, or a request sent by the terminal in response to a specificoperation of a user, such as a query operation, an operation of openingan information stream data display page, or an operation of refreshing apage displaying information stream data. As an example, after a userinputs a query statement in a search bar, a stream data acquisitionrequest may be sent to a server by clicking a query button or pressingan enter key; or when a user is browsing a page displaying informationstream data, a stream data acquisition request may be sent to a serverby a gesture of sliding down or clicking on an area for indicating arefresh operation, to acquire unread information stream data.

By clicking on the area displaying the information stream data, the pagepointed to by the information stream data may be accessed. Theinformation stream data may be interpreted as data obtained byintegrating the page pointed to by the information stream data, and mayinclude the title of content of the page pointed to by the informationstream data, a page link pointed to by the information stream data,description information of content of the page pointed to by theinformation stream data, etc., such as a search result in a searchresult page, or a message or a trend issued by a user in a socialapplication.

The information stream data acquisition request includes queryinformation, the query information may be information for indicating howto acquire first information stream data, and the first informationstream data may be information stream data subscribed or queried by theuser. As an example, the query information may be a query statementinput by the user, or account information of an account associated withthe terminal, such as an account identifier. A subscription list or aninterest list of the account may be acquired from a database via theaccount identifier, and data issued by the account in the list may befurther acquired.

Step 202: performing a query according to the query information toobtain first information stream data.

In this embodiment, the above electronic device may perform a queryaccording to the query information acquired in step 201, to obtain firstinformation stream data. As an example, the above electronic device mayquery, in a corresponding database, the information stream data matchingthe query statement input by the user as the first information streamdata; the above electronic device may also first query the interest listof the account associated with the terminal that sends the informationstream data acquisition request, to obtain the identifier of an accountof interest, then query the information published by the account ofinterest according to the identifier of the account of interest, and usethe information that has not been pushed to the terminal in theinformation published by the account of interest as the firstinformation stream data.

Step 203: acquiring a search record and/or a browsing record of anaccount associated with the terminal, the search record and/or thebrowsing record being within a predetermined time period.

In this embodiment, the above electronic device may acquire a searchrecord and/or a browsing record of an account associated with theterminal, the search record and/or the browsing record being within apredetermined time period. The account associated with the terminal maybe an account currently logged in on the terminal, or an accountestablished according to device information of the terminal or otherassociated information, e.g., an account established according to IMEI(International Mobile Equipment Identity) or SIM (SubscriberIdentification Module). The predetermined time period may be the recenttime period, e.g., the past few weeks, or the past few days.Specifically, the predetermined time period may be set according toactual needs, and when many search records and/or browsing records areprovided, the predetermined time period may be appropriately shortened.The search record may be a search record of the account associated withthe terminal in a search engine, or a search record of the accountassociated with the terminal in other application. The browsing recordmay be a record of the pages that the user has visited in theapplication adopting the information stream data system, the pages beingpointed to by the information stream data.

Step 204: determining a keyword based on the search record and/or thebrowsing record.

In this embodiment, the above electronic device may determine a keywordbased on the search record and/or the browsing record acquired in step203. The above electronic device may directly extract from the searchrecord a search word input by the user, or extract from the browsingrecord a title or a label of a page browsed by the user, and segment thesearch word, the title or the label to obtain a keyword. When too manywords are obtained, some screening operations may be performed, toprevent excessive keywords from affecting the execution efficiency ofsubsequent steps of the information.

Step 205: determining, in a preset information stream data set, secondinformation stream data matching the keyword.

In this embodiment, the above electronic device may determine, in apreset information stream data set, second information stream datamatching the keyword determined in step 204. The preset informationstream data set may be an information stream data set pre-stored in adatabase associated with the electronic device, or a set of a number ofinformation stream data used for promotion, e.g., advertisement data.The above electronic device may generate a query message (Query) basedon the keyword, send the generated query message to the database storingthe preset information stream data set, and determine the informationstream data returned by the database as the second information streamdata matching the keyword. The second stream data matching the keywordmay be information stream data including the keyword or an expanded wordof the keyword. Alternatively, a label may be preset for each piece ofthe information stream data in the information stream data set, as anexample, an enterprise needs to publish promotion information, and whenthe promotion information provided is acquired, the label set for thepromotion information may be acquired. For example, if a brand is goingto promote a mobile phone, the mobile phone, dual cameras, the name ofthe brand and the names of other mobile phone brands may be set aslabels while the introduction information of the mobile phone isprovided.

Step 206: generating to-be-pushed data based on the first informationstream data and the determined second information stream data.

In this embodiment, the above electronic device may generateto-be-pushed data base on the first information stream data and thesecond information stream data determined in step 205. The electronicdevice may aggregate, according to the layout information of a terminalpage, the first information stream data and the determined secondinformation stream data to generate to-be-pushed data. The layoutinformation may be used to indicate the number of information streamdata displayed on the page, and the distribution of the firstinformation stream data and the determined second information streamdata, for example, one piece of determined second information streamdata is inserted every certain number of first information stream data.

Step 207: pushing the to-be-pushed data to the terminal.

In this embodiment, the above electronic device may push theto-be-pushed data generated in step 206 to the terminal through thenetwork, for display by the terminal.

The method provided by the above embodiment of the present disclosurerealizes targeted information push by receiving an information streamdata acquisition request sent by a terminal, performing a queryaccording to the query information to obtain first information streamdata, then acquiring a search record and a browsing record of an accountassociated with the terminal, the search record and/or the browsingrecord being within a predetermined time period, determining a keywordon the basis of the search record and/or the browsing record,determining, in a preset information stream data set, second informationstream data matching the keyword, finally generating to-be-pushed databased on the first information stream data and the determined secondinformation stream data, and pushing the to-be-pushed data to theterminal.

In some optional implementations of this embodiment, the generatingto-be-pushed data based on the first information stream data and thedetermined second information stream data includes: in response thenumber of the determined second information stream data being greaterthan a preset number, executing the following score determinationoperation for each piece of second information stream data in thedetermined second information stream data: acquiring a preset attributevalue corresponding to the second information stream data; respectivelydetermining, on the basis of a pre-trained second probabilitydetermination model, a second probability of receiving a request sent bythe terminal for visiting a page pointed to by the second informationstream data; selecting, from the determined second information streamdata, a preset number of second information stream data according to anorder of the scores from high to low; and aggregating the firstinformation stream data and the selected second information stream datato generate to-be-pushed data.

In this implementation, the preset number may be the number of thesecond information stream data displayed on the indication page in thelayout information of the terminal page, and may be specifically setaccording to actual needs. The attribute value corresponding to theinformation stream data may be a parameter value for characterizing thefeature thereof, for example, the information stream data isadvertisement data, and the attribute value corresponding to theadvertisement data may be a bid of a customer for the advertisementdata, or the number of clicks or pushes on the advertisement data, etc.

The second probability determination model may be used to characterize acorresponding relationship between at least one of the followinginformation items and the second probability: account information of anaccount associated with the terminal, a device type of the terminal,type information of a browser used by the terminal, or featureinformation of the second information stream data. The accountinformation of the account associated with the terminal may beinformation such as age, occupation, location, hobbies, accounts ofinterest, or subscribed columns. The feature information of the secondinformation stream data may be information for characterizing the corecontent of the second information stream data, and may be obtained bysemantic analysis on the second information stream data. The featureinformation may also be preset for the second information stream data,for example, the second information stream data is promotioninformation, and the feature information thereof may be a label set by aparty providing the promotion information.

As an example, the above electronic device may train a model forclassification such as an initial Naive Bayesian Model (NBM) or aSupport Vector Machine (SVM) by using each of the above informationitems recorded in historical records as inputs, and using the ratios,obtained according to the historical record statistic, of receiving therequest for visiting the pages pointed to by the second informationstream data as outputs, to obtain the second probability determinationmodel. The second probability determination model may also be acorresponding relationship table being previously created by atechnician on the basis of the statistics on a large amount of the aboveinformation items and the second probability and storing correspondingrelationships between the plurality of information items and the secondprobability; or a calculation formula preset by a technician on thebasis of statistics on a large amount of data and stored into theelectronic device, where the calculation formula quantifies andcalculates one or more of the information items to obtain a calculationresult used for characterizing the second probability, for example, thecalculation formula may be a formula for calculating the correlationbetween the account information and the feature information, and if theobtained correlation is high, then the second probability is large.

In this implementation, the determining the score of the secondinformation stream data based on the acquired attribute value and thesecond probability, may be calculating a product of the acquiredattribute value and the second probability as the score of the secondinformation stream data, or normalizing the attribute value, weightedsumming based on preset weights the normalized value and the secondprobability to obtain the score of the second information stream data.

Refer to FIG. 3, which is a process diagram of another embodiment of themethod for pushing information.

In FIG. 3, the process 300 of the method for pushing informationincludes the following steps:

Step 301: receiving an information stream data acquisition request sentby a terminal.

In this embodiment, an electronic device (e.g., the server shown inFIG. 1) on which the method for pushing information runs may receive aninformation stream data acquisition request sent by a terminal.

Step 302: performing a query according to the query information toobtain first information stream data.

In this embodiment, the electronic device may perform the queryaccording to the query information acquired in step 301 to obtain firstinformation stream data.

Step 303: acquiring a search record and/or a browsing record of anaccount associated with the terminal, the search record and/or thebrowsing record being within a predetermined time period.

In this embodiment, the electronic device may acquire a search recordand/or a browsing record of an account associated with the terminal, thesearch record and/or the browsing record being a predetermined timeperiod.

Step 304: acquiring a search statement in the search record and/orcontent of a page browsed in the browsing record.

In this embodiment, the electronic device may acquire a search statementin the search record acquired in step 303 and/or the content of a pagebrowsed in the browsing record.

Step 305: parsing the search statement and/or the content to obtain analternative word set.

In this embodiment, the electronic device may parse the search statementand/or content acquired in step 304 to obtain an alternative word set.The parsing the search statement and/or content to obtain an alternativeword set may include: performing statistical analysis and/or semanticparsing on the search statement and/or the content, to extract at leastone core word; expanding each core word in the at least one core word toobtain an expanded word, where the expanded word includes at least oneof the following: a synonym of the core word, a near-synonym of the coreword, or an associated word of the core word; and determining the coreword and the obtained expanded word as keywords. As an example, in theexpanding operation, the core word “children” may have a synonym “kids”;the core word “Chinese medicine” may have a near-synonym “herb”, and“attendance” may have a near-synonym “participation”; the core word“cold” may have an associated word “fever” or “influenza”, and brandnames of different brands producing the same product or names ofdifferent products under the same brand may also be mutually associatedwords.

As an example, the statistical analysis may include counting and rankingthe occurrence frequency of each word being there in the searchstatement and/or the content, and then selecting one or more words withthe highest frequency of occurrence as keywords. The semantic parsingmay include segmenting the content into words by processing the content,such as omni-segmenting the content, then calculating the importance ofthe obtained words (for example, using the method of TermFrequency-Inverse Document Frequency (TF-IDF)), and obtaining keywordsbased on the result of the importance calculation. Through the expandingoperation, the keywords are richer, and the accuracy of information pushis further improved.

Step 306: for each alternative word in the alternative word set,determining, in a preset information stream data set, second informationstream data matching the alternative word, and determining, on the basisof a pre-trained first probability determination model, a firstprobability of receiving a visit request for a page sent by theterminal.

In this embodiment, the electronic device may first determine in apreset information stream data set, for each alternative word in thealternative word set obtained in step 305, second information streamdata matching the alternative word; then acquire input data required bya first probability model, and import the input data into a pre-trainedfirst probability determination model to determine a first probabilityof receiving a visit request for pages sent by the terminal, the pageincluding a page pointed to by the second information stream datamatching the alternative word.

The first probability determination model may be used to characterize acorresponding relationship between at least one of the followinginformation items and the first probability: account information of anaccount associated with the terminal, a device type of the terminal, abrowser type of a browser used by the terminal, alternative words,information of an industry to which the alternative words belong, orsource of the alternative words. The information of the industry of thealternative words may be information for characterizing the industry orfield of the alternative words, such as the automobile industry, or themobile phone industry. The source of the alternative words is used tocharacterize the source of the alternative words, for example, a searchstatement input by a user, or a browsing record.

As an example, the electronic device may train a model forclassification such as an initial naive Bayesian model or a supportvector machine by using each of the above information items recorded inhistorical records as inputs, and using the ratios, obtained accordingto the historical record statistic, of receiving the request forvisiting the pages pointed to by the first information stream data asoutputs, to obtain the first probability determination model. The firstprobability determination model may also be a corresponding relationshiptable being previously created by a technician on the basis of thestatistics on a large amount of the above information items and thefirst probability and storing corresponding relationships between theplurality of information items and the first probability; or acalculation formula preset by a technician on the basis of statistics ona large amount of data and stored into the electronic device, where thecalculation formula quantifies and calculates one or more of theinformation items to obtain a calculation result used for characterizingthe first probability, for example, the calculation formula may be aformula for calculating the correlation between the hobbies oroccupation in the account information of the account associated with theterminal and the industry information of the industry of the alternativewords, and if the obtained correlation is high, then the firstprobability is large.

Step 307: executing a score determination operation for each alternativeword in the alternative word set.

In this embodiment, for each piece of information stream data in thepreset information stream data set, an attribute value corresponding tothe information stream data is preset. The score determination operationexecuted by the electronic device for each alternative word in thealternative word set obtained in step 305 may include: acquiring apreset attribute value corresponding to the second information streamdata matching the alternative word, and determining, based on theacquired attribute value, an attribute value corresponding to thealternative word; calculating a product of the attribute valuecorresponding to the alternative word and the first probabilitycorresponding to the alternative word determined in step 306; acquiringweights preset for the first probability, the attribute value and theproduct, and performing, based on the acquired weights, weightedsummation on the attribute value corresponding to the alternative word,the first probability corresponding to the alternative word, and theproduct to obtain a score corresponding to the alternative word.

In this embodiment, there may be multiple pieces of second informationstream data matching the alternative word, each piece of secondinformation stream data has an attribute value corresponding thereto,and an average value of the multiple attribute values may be used as theattribute value corresponding to the alternative word, or the highestattribute value is used as the attribute value corresponding to thealternative word. Scores corresponding to respective alternative wordsare obtained by a method of multi-target fusion. A set of initialweights may be set by analyzing the average value of the both, and thenthe weights are continuously adjusted according to actual needs. A setof superior weights is finally obtained. For example, the scorecorresponding to the alternative word may be calculated via thefollowing formula:S=W ₁ ×P+W ₂ ×V+W ₃ ×P×V;  (1)

Where S represents a score corresponding to an alternative word, Prepresents a first probability corresponding to the alternative word, Vrepresents an attribute value corresponding to the alternative word, W₁represents a weight set for the first probability, W₂ represents aweight set for the attribute value, and W₃ represents a weight set forthe product of the first probability and the attribute value.

Step 308: selecting, from respective alternative words of thealternative word set, a predetermined number of alternative words askeywords according to an order of the scores from high to low.

In this embodiment, the electronic device may select a predeterminednumber of alternative words as keywords from the respective alternativewords of the alternative word set according to an order of the scoresobtained in step 307 from high to low. The predetermined number may bedetermined according to the amount of computation bearable for thesystem, and an excessive predetermined number may affect the efficiencyof information push. As an example, the predetermined number may be two.

Step 309: determining, in the preset information stream data set, secondinformation stream data matching the keyword.

In this embodiment, the electronic device may determine secondinformation stream data matching the keywords determined in step 308 inthe preset information stream data set.

Step 310: generating to-be-pushed data based on the first informationstream data and the determined second information stream data.

In this embodiment, the electronic device may generate to-be-pushed databased on the first information stream data and the second informationstream data determined in step 309.

Step 311: pushing the to-be-pushed data to the terminal.

In this embodiment, the electronic device may push the to-be-pushed datagenerated in step 310 to the terminal through the network for display bythe terminal.

The implementation details and technical effects of steps 301-303 andsteps 309-311 may refer to the descriptions insteps 201-203 and steps205-207, and details are not described herein again.

It may be seen from FIG. 3 that, compared with the correspondingembodiment of FIG. 2, the process 300 of the method for pushinginformation in the present embodiment highlights the step of determiningkeywords. Thus, the solution described in this embodiment may determinea keyword most fit with the user's need, thereby achieving moreefficient information push.

Continue to refer to FIG. 4, which is a schematic diagram of anapplication scenario of the method for pushing information according toan embodiment. In the application scenario of FIG. 4, when the currentpage does not include information stream data that the user has notread, the user sends an information stream data acquisition request tothe server through the terminal by a gesture operation of pressing andsliding down. Through an account identifier included in the request, theserver finds a user's subscription list, and acquires, according to thesubscription list, unread information stream data subscribed by the useras first information stream data. The server also finds a user's searchrecord and/or browsing record within a predetermined time period via theaccount identifier, and discovers that the user has searched for “priceof certain brand mobile phone” or “release time of certain brand mobilephone”, or the user has browsed a page entitled “top ten reasons forbuying a mobile phone of certain brand” or “mobile phone performancecomparison.” The “certain brand”, “mobile phone”, other mobile phonebrands with similar prices, or product names of other products undercertain brand may be determined as keywords, for querying the secondinformation stream data matching the keywords in a preset promotion dataset is queried. Finally, to-be-pushed data is generated based on thefirst information stream data and the determined second informationstream data, and the to-be-pushed data is pushed to the terminal.

Further refer to FIG. 5, as an implementation of the method, the presentdisclosure provides an embodiment of an apparatus for pushinginformation, the embodiment of the apparatus corresponds to theembodiment of the method shown in FIG. 2, and the apparatus may bespecifically applied to various types of electronic devices.

As shown in FIG. 5, the apparatus 500 for pushing information in thisembodiment includes: a receiving unit 501, a query unit 502, anacquisition unit 503, a first determination unit 504, a seconddetermination unit 505, a generation unit 506, and a push unit 507,where the receiving unit 501 is configured to receive an informationstream data acquisition request sent by a terminal, the informationstream data acquisition request including query information; the queryunit 502 is configured to perform a query according to the queryinformation to obtain first information stream data; the acquisitionunit 503 is configured to acquire a search record and/or a browsingrecord of an account associated with the terminal, the search recordand/or the browsing record being within a predetermined time period; thefirst determination unit 504 is configured to determine a keyword basedon the search record and/or the browsing record; the seconddetermination unit 505 is configured to determine second informationstream data matching the keyword in a preset information stream dataset; the generation unit 506 is configured to generate to-be-pushed databased on the first information stream data and the determined secondinformation stream data; and the push unit 507 is configured to push theto-be-pushed data to the terminal.

In this embodiment, the specific processing of the receiving unit 501,the query unit 502, the acquisition unit 503, the first determinationunit 504, the second determination unit 505, the generation unit 506,and the push unit 507 may refer to steps 201, 202, 203, 204, 205, 206,and 207 of the corresponding embodiment in FIG. 2, and details are notdescribed herein again.

In some optional implementations of this embodiment, the firstdetermination unit 504 includes: an acquisition subunit (not shown),configured to acquire a search statement in the search record and/orcontent of a browsed page in the browsing record; a parsing subunit (notshown), configured to parse the search statement and/or the content, toobtain an alternative word set; a first determination subunit (notshown), configured to determine, for each alternative word in thealternative word set, second information stream data matching thealternative word in a preset information stream data set, and determine,on the basis of a pre-trained first probability determination model, afirst probability of receiving a visit request for a page sent by theterminal, where the page includes a page pointed to by the secondinformation stream data matching the alternative word, and the firstprobability determination model is used to characterize a correspondingrelationship between at least one of the following information items andthe first probability: account information of an account associated withthe terminal, a device type of the terminal, a browser type of a browserused by the terminal, the alternative word, information of an industryto which the alternative word belongs, or source the alternative word;and a first selection subunit (not shown), configured to select thekeyword from the alternative word set based on the first probability.

In some optional implementations of this embodiment, for each piece ofinformation stream data in the preset information stream data set, anattribute value corresponding to the piece of information stream data ispreset; and the first selection subunit (not shown) includes: a firstdetermination module (not shown), configured to execute the followingscore determination operations for each alternative word in thealternative word set: acquiring a preset attribute value correspondingto the second information stream data matching the alternative word, anddetermining, based on the acquired attribute value, an attribute valuecorresponding to the alternative word; calculating a product of theattribute value corresponding to the alternative word and the firstprobability corresponding to the alternative word; acquiring weightspreset for the first probability, the attribute value and the product,and performing, based on the acquired weights, weighted summation on theattribute value corresponding to the alternative word, the firstprobability corresponding to the alternative word, and the product toobtain a score corresponding to the alternative word; and a selectionmodule (not shown), configured to select a predetermined number ofalternative words as keywords from the respective alternative words ofthe alternative word set according to an order of the scores from highto low.

In some optional implementations of this embodiment, the analysissubunit (not shown) includes: an analysis module (not shown), configuredto perform statistical analysis and/or semantic parsing on the searchstatement and/or content to extract at least one core word; an expansionmodule (not shown), configured to expand each core word in the at leastone core word to obtain an expanded word, where the expanded wordincludes at least one of the following: a synonym of the core word, anear-synonym of the core word, or an associated word of the core word;and a second determination module (not shown), configured to determinethe core word and the obtained expanded word as keywords.

In some optional implementations of this embodiment, the generation unit506 includes: a second determination subunit (not shown), configured toexecute, in response to the number of the determined second informationstream data being greater than a preset number, the following scoredetermination operation for each piece of second information stream datain the determined second information stream data: acquiring a presetattribute value corresponding to the second information stream data;respectively determining, on the basis of a pre-trained secondprobability determination model, a second probability of receiving therequest sent by the terminal for visiting a page pointed by the secondinformation stream data, where the second probability determinationmodel is used to characterize a corresponding relationship between atleast one of the following information items and the second probability:account information of an account associated with the terminal, a devicetype of the terminal, type information of a browser used by theterminal, or feature information of the second information stream data;and determining a score of the second information stream data based onthe acquired attribute value and the second probability; a secondselection subunit (not shown), configured to select a preset number ofsecond information stream data from the determined second informationstream data according to an order of the scores from high to low; and anaggregation subunit (not shown), configured to aggregate the firstinformation stream data and the selected second information stream datato generate to-be-pushed data.

It may be seen from FIG. 5 that the apparatus 500 for pushinginformation in this embodiment realizes targeted information push byreceiving an information stream data acquisition request sent by aterminal, performing a query according to the query information toobtain first information stream data, then acquiring a search record anda browsing record of an account associated with the terminal, the searchrecord and/or the browsing record being within a predetermined timeperiod, determining a keyword based on the search record and/or thebrowsing record, determining second information stream data matching thekeyword in a preset information stream data set, finally generatingto-be-pushed data based on the first information stream data and thedetermined second information stream data, and pushing the to-be-pusheddata to the terminal.

Referring to FIG. 6, a schematic structural diagram of a computer system600 adapted to implement the server of some embodiments is shown. Theserver shown in FIG. 6 is merely an example, and should not limit thefunction and scope of use of the embodiments of the present disclosure.

As shown in FIG. 6, the computer system 600 includes a centralprocessing unit (CPU) 601, which may execute various appropriate actionsand processes in accordance with a program stored in a read-only memory(ROM) 602 or a program loaded into a random access memory (RAM) 603 froma storage portion 608. The RAM 603 also stores various programs and datarequired by operations of the system 600. The CPU 601, the ROM 602 andthe RAM 603 are connected to each other through a bus 604. Aninput/output (I/O) interface 605 is also connected to the bus 604.

The following components are connected to the I/O interface 605: aninput portion 606 including a keyboard, a mouse, etc.; an output portion607 including such as a cathode ray tube (CRT), a liquid crystal displaydevice (LCD), a speaker, etc.; a storage portion 608 including a harddisk and the like; and a communication portion 609 including a networkinterface card, such as a LAN card and a modem. The communicationportion 609 performs communication processes via a network, such as theInternet. A driver 610 is also connected to the I/O interface 605 asrequired. A removable medium 611, such as a magnetic disk, an opticaldisk, a magneto-optical disk, and a semiconductor memory, may beinstalled on the driver 610, to facilitate the retrieval of a computerprogram from the removable medium 611, and the installation thereof onthe storage portion 608 as needed.

In particular, according to the embodiments of the present disclosure,the process described above with reference to the flow chart may beimplemented in a computer software program. For example, an embodimentof the present disclosure includes a computer program product, whichincludes a computer program that is tangibly embedded in acomputer-readable medium. The computer program includes program codesfor executing the method as illustrated in the flow chart. In such anembodiment, the computer program may be downloaded and installed from anetwork via the communication portion 609, and/or may be installed fromthe removable medium 611. The computer program, when executed by thecentral processing unit (CPU) 601, implements the above mentionedfunctionalities as defined by the method of some embodiments of thepresent disclosure. It should be noted that the computer readable mediumin some embodiments of the present disclosure may be computer readablesignal medium or computer readable storage medium or any combination ofthe above two. An example of the computer readable storage medium mayinclude, but not limited to: electric, magnetic, optical,electromagnetic, infrared, or semiconductor systems, apparatus,elements, or a combination of any of the above. A more specific exampleof the computer readable storage medium may include but is not limitedto: electrical connection with one or more wire, a portable computerdisk, a hard disk, a random access memory (RAM), a read only memory(ROM), an erasable programmable read only memory (EPROM or flashmemory), a fibre, a portable compact disk read only memory (CD-ROM), anoptical memory, a magnet memory or any suitable combination of theabove. In some embodiments of the present disclosure, the computerreadable storage medium may be any physical medium containing or storingprograms which may be used by a command execution system, apparatus orelement or incorporated thereto. In some embodiments of the presentdisclosure, the computer readable signal medium may include data signalin the base band or propagating as parts of a carrier, in which computerreadable program codes are carried. The propagating data signal may takevarious forms, including but not limited to: an electromagnetic signal,an optical signal or any suitable combination of the above. The signalmedium that can be read by computer may be any computer readable mediumexcept for the computer readable storage medium. The computer readablemedium is capable of transmitting, propagating or transferring programsfor use by, or used in combination with, a command execution system,apparatus or element. The program codes contained on the computerreadable medium may be transmitted with any suitable medium includingbut not limited to: wireless, wired, optical cable, RF medium etc., orany suitable combination of the above.

The flow charts and block diagrams in the accompanying drawingsillustrate architectures, functions and operations that may beimplemented according to the systems, methods and computer programproducts of the various embodiments of the present disclosure. In thisregard, each of the blocks in the flow charts or block diagrams mayrepresent a module, a program segment, or a code portion, said module,program segment, or code portion including one or more executableinstructions for implementing specified logic functions. It should alsobe noted that, in some alternative implementations, the functionsdenoted by the blocks may occur in a sequence different from thesequences shown in the accompanying drawings. For example, any twoblocks presented in succession may be executed, substantially inparallel, or they may sometimes be in a reverse sequence, depending onthe function involved. It should also be noted that each block in theblock diagrams and/or flow charts as well as a combination of blocks maybe implemented using a dedicated hardware-based system executingspecified functions or operations, or by a combination of a dedicatedhardware and computer instructions.

The units involved in the embodiments of the present disclosure may beimplemented by means of software or hardware. The described units mayalso be provided in a processor, for example, described as: a processor,including a receiving unit, a query unit, an acquisition unit, a firstdetermination unit, a second determination unit, a generation unit, apush unit. Here, the names of these units do not in some casesconstitute a limitation to such units themselves. For example, thereceiving unit may also be described as “a unit for receiving aninformation stream data acquisition request sent by a terminal.”

In another aspect, the present disclosure further provides a computerreadable medium. The computer readable medium may be included in theelectronic device in the above described embodiments, or a stand-alonecomputer readable medium not assembled into the electronic device. Thecomputer readable medium carries one or more programs. The one or moreprograms, when executed by the electronic device, cause the electronicdevice to: receiving an information stream data acquisition request sentby a terminal, the information stream data acquisition requestcomprising query information; performing a query according to the queryinformation to obtain first information stream data; acquiring a searchrecord and/or a browsing record of an account associated with theterminal, the search record and/or the browsing record being within apredetermined time period; determining a keyword based on the searchrecord and/or the browsing record; determining, in a preset informationstream data set, second information stream data matching the keyword;generating to-be-pushed data based on the first information stream dataand the determined second information stream data; and pushing theto-be-pushed data to the terminal.

The above description only provides an explanation of the preferredembodiments of the present disclosure and the technical principles used.It should be appreciated by those skilled in the art that the inventivescope of the present disclosure is not limited to the technicalsolutions formed by the particular combinations of the above-describedtechnical features. The inventive scope should also cover othertechnical solutions formed by any combinations of the above-describedtechnical features or equivalent features thereof without departing fromthe concept of the present disclosure. Technical schemes formed by theabove-described features being interchanged with, but not limited to,technical features with similar functions disclosed in the presentdisclosure are examples.

What is claimed is:
 1. A method for pushing information, the methodcomprising: in response to an information stream data acquisitionrequest sent by a terminal, performing a query to obtain firstinformation stream data; obtaining an alternative word set based on atleast one of search statement in a search record or content of a browsedpage in a browsing record; for each alternative word in the alternativeword set: determining second information stream data and a presetattribute value corresponding to the second information stream datamatching the alternative word; calculating a product of the presetattribute value corresponding to the alternative word and a firstprobability corresponding to the alternative word; obtaining a firstscore corresponding to the alternative word by weighted summation on thepreset attribute value, the first probability, and the product; andselecting, from the alternative word set, a predetermined number ofalternative words as keywords according to an order of the first scoresfrom high to low; determining, in a preset information stream data set,second information stream data matching the selected keywords; inresponse to a number of the determined second information stream datamatching the selected keywords being greater than a preset number,executing following operations for each piece of the determined secondinformation stream data matching the selected keywords: acquiringanother preset attribute value corresponding to the second informationstream data matching the selected keywords; determining respectively, ona basis of a pre-trained second probability determination model, asecond probability of receiving a request sent by the terminal forvisiting a page pointed to by the second information stream datamatching the selected keywords, wherein the second probabilitydetermination model is used to characterize a corresponding relationshipbetween the second probability and at least one of following informationitems: an account information of an account associated with theterminal, a device type of the terminal, type information of a browserused by the terminal, or feature information of the second informationstream data matching the selected keywords; and determining a secondscore of the second information stream data matching the selectedkeywords based on the other acquired preset attribute value and thesecond probability; selecting, from the determined second informationstream data matching the selected keywords, the preset number of thesecond information stream data matching the selected keywords accordingto an order of the second scores from high to low; aggregating the firstinformation stream data and the selected second information stream datato generate to-be-pushed data; and pushing the to-be-pushed data to theterminal.
 2. The method according to claim 1, wherein: the firstprobability is determined, on a basis of a pre-trained first probabilitydetermination model, which is used to characterize a correspondingrelationship between the first probability and at least one of followinginformation items: the account information of an account associated withthe terminal, the device type of the terminal, the browser type of thebrowser used by the terminal, the alternative word, information of anindustry to which the alternative word belongs, or a source of thealternative word.
 3. The method according to claim 2, wherein obtainingthe alternative word set comprises: performing at least one ofstatistical analysis or semantic parsing on the at least one of thesearch statement or the content, to extract at least one core word;expanding each core word in the at least one core word to obtain anexpanded word, wherein the expanded word comprises at least one of thefollowing: a synonym of the core word, a near-synonym of the core word,or an associated word of the core word; and determining the core wordand the obtained expanded word as the selected keywords.
 4. An apparatusfor pushing information, the apparatus comprising: at least oneprocessor; and a memory storing instructions, the instructions whenexecuted by the at least one processor, cause the at least one processorto perform operations, the operations comprising: in response to aninformation stream data acquisition request sent by a terminal,performing a query to obtain first information stream data; obtaining analternative word set based on at least one of search statement in asearch record or content of a browsed page in a browsing record; foreach alternative word in the alternative word set: determining secondinformation stream data and a preset attribute value corresponding tothe second information stream data matching the alternative word;calculating a product of the preset attribute value corresponding to thealternative word and a first probability corresponding to thealternative word; obtaining a first score corresponding to thealternative word by weighted summation on the preset attribute value,the first probability, and the product; and selecting, from thealternative word set, a predetermined number of alternative words askeywords according to an order of the first scores from high to low;determining, in a preset information stream data set, second informationstream data matching the selected keywords; in response to a number ofthe determined second information stream data matching the selectedkeywords being greater than a preset number, executing followingoperations for each piece of the determined second information streamdata matching the selected keywords: acquiring another preset attributevalue corresponding to the second information stream data matching theselected keywords; determining respectively, on a basis of a pre-trainedsecond probability determination model, a second probability ofreceiving a request sent by the terminal for visiting a page pointed toby the second information stream data matching the selected keywords,wherein the second probability determination model is used tocharacterize a corresponding relationship between the second probabilityand at least one of following information items: an account informationof an account associated with the terminal, a device type of theterminal, type information of a browser used by the terminal, or featureinformation of the second information stream data matching the selectedkeywords; and determining a second score of the second informationstream data matching the selected keywords based on the other acquiredpreset attribute value and the second probability; selecting, from thedetermined second information stream data matching the selectedkeywords, the preset number of the second information stream datamatching the selected keywords according to an order of the secondscores from high to low; aggregating the first information stream dataand the selected second information stream data to generate to-be-pusheddata; and pushing the to-be-pushed data to the terminal.
 5. Theapparatus according to claim 4, wherein: the first probability isdetermined, on a basis of a pre-trained first probability determinationmodel, which is used to characterize a corresponding relationshipbetween the first probability and at least one of following informationitems: the account information of an account associated with theterminal, the device type of the terminal, the browser type of thebrowser used by the terminal, the alternative word, information of anindustry to which the alternative word belongs, or a source of thealternative word.
 6. The apparatus according to claim 5, whereinobtaining the alternative word set comprises: performing at least one ofstatistical analysis or semantic parsing on the at least one of thesearch statement or the content, to extract at least one core word;expanding each core word in the at least one core word to obtain anexpanded word, wherein the expanded word comprises at least one of thefollowing: a synonym of the core word, a near-synonym of the core word,or an associated word of the core word; and determining the core wordand the obtained expanded word as the selected keywords.
 7. Anon-transitory computer readable storage medium storing a computerprogram, wherein the computer program, when executed by a processor,causes the processor to perform operations, the operations comprising:in response to an information stream data acquisition request sent by aterminal, performing a query to obtain first information stream data;obtaining an alternative word set based on at least one of searchstatement in a search record or content of a browsed page in a browsingrecord; for each alternative word in the alternative word set:determining second information stream data and a preset attribute valuecorresponding to the second information stream data matching thealternative word; calculating a product of the preset attribute valuecorresponding to the alternative word and a first probabilitycorresponding to the alternative word; obtaining a first scorecorresponding to the alternative word by weighted summation on thepreset attribute value, the first probability, and the product; andselecting, from the alternative word set, a predetermined number ofalternative words as keywords according to an order of the first scoresfrom high to low; determining, in a preset information stream data set,second information stream data matching the selected keywords; inresponse to a number of the determined second information stream datamatching the selected keywords being greater than a preset number,executing following operations for each piece of the determined secondinformation stream data matching the selected keywords: acquiringanother preset attribute value corresponding to the second informationstream data matching the selected keywords; determining respectively, ona basis of a pre-trained second probability determination model, asecond probability of receiving a request sent by the terminal forvisiting a page pointed to by the second information stream datamatching the selected keywords, wherein the second probabilitydetermination model is used to characterize a corresponding relationshipbetween the second probability and at least one of following informationitems: an account information of an account associated with theterminal, a device type of the terminal, type information of a browserused by the terminal, or feature information of the second informationstream data matching the selected keywords; and determining a secondscore of the second information stream data matching the selectedkeywords based on the other acquired preset attribute value and thesecond probability; selecting, from the determined second informationstream data matching the selected keywords, the preset number of thesecond information stream data matching the selected keywords accordingto an order of the second scores from high to low; aggregating the firstinformation stream data and the selected second information stream datato generate to-be-pushed data; and pushing the to-be-pushed data to theterminal.
 8. The medium according to claim 7, wherein: the firstprobability is determined, on a basis of a pre-trained first probabilitydetermination model, which is used to characterize a correspondingrelationship between the first probability and at least one of followinginformation items: the account information of an account associated withthe terminal, the device type of the terminal, the browser type of thebrowser used by the terminal, the alternative word, information of anindustry to which the alternative word belongs, or a source of thealternative word.
 9. The medium according to claim 8, wherein obtainingthe alternative word set comprises: performing at least one ofstatistical analysis or semantic parsing on the at least one of thesearch statement or the content, to extract at least one core word;expanding each core word in the at least one core word to obtain anexpanded word, wherein the expanded word comprises at least one of thefollowing: a synonym of the core word, a near-synonym of the core word,or an associated word of the core word; and determining the core wordand the obtained expanded word as the selected keywords.